A Bargaining Game-Based Human–Machine Shared Driving Control Authority Allocation Strategy-Reference-Cited by-同舟云学术

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A Bargaining Game-Based Human–Machine Shared Driving Control Authority Allocation Strategy

Published:2023-10 Issue:10 Volume:24 Page:10572-10586
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Dai Changhua¹^ORCID,Zong Changfu¹,Zhang Dong²,Hua Min³,Zheng Hongyu¹^ORCID,Chuyo Kaku⁴^ORCID

Affiliation:

1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, China

2. Department of Mechanical and Aerospace Engineering, Brunel University London, London, U.K

3. School of Engineering, University of Birmingham, Birmingham, U.K

4. Jiangsu Chaoli Electric Company Ltd, Danyang, China

Funder

Open Foundation of the State Key Laboratory of Automotive Simulation and Control

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10271405/10136225.pdf?arnumber=10136225

Reference31 articles.

1. Motor learning affects car-to-driver handover in automated vehicles

2. MPC-based switched driving model for human vehicle co-piloting considering human factors

3. Toward human-vehicle collaboration: Review and perspectives on human-centered collaborative automated driving

4. When the automated driving system fails: Dynamics of public responses to automated vehicles

5. A Novel Adaptive Steering Torque Control Approach for Human–Machine Cooperation Autonomous Vehicles

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4. Experimenting With an Efficient Driver Behavior Dynamical Model Applicable to Simulated Lane Changing Tasks;IEEE Access;2024

5. A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles;IEEE Internet of Things Journal;2023-12-15

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